An overview of artificial intelligence applications for power electronics

S Zhao, F Blaabjerg, H Wang - IEEE Transactions on Power …, 2020 - ieeexplore.ieee.org
This article gives an overview of the artificial intelligence (AI) applications for power
electronic systems. The three distinctive life-cycle phases, design, control, and maintenance …

Sliding mode control in power converters and drives: A review

L Wu, J Liu, S Vazquez… - IEEE/CAA Journal of …, 2021 - ieeexplore.ieee.org
Sliding mode control (SMC) has been studied since the 1950s and widely used in practical
applications due to its insensitivity to matched disturbances. The aim of this paper is to …

Lifetime extension approach based on the Levenberg–Marquardt neural network and power routing of DC–DC converters

J Zhang, J Tian, AM Alcaide, JI Leon… - … on Power Electronics, 2023 - ieeexplore.ieee.org
The power conversion system based on the modular connection has widespread
applications in various power electronic systems. To accurately estimate the state of health …

Observer-based fixed-time control for permanent-magnet synchronous motors with parameter uncertainties

X Lin, C Wu, W Yao, Z Liu, X Shen, R Xu… - … on Power Electronics, 2022 - ieeexplore.ieee.org
In this article, a fixed-time observer-based sliding-mode control strategy is proposed for a
permanent-magnet synchronous motor. Both the current regulation loop (inner loop) and the …

Sliding mode control: Overview of its applications in power converters

H Komurcugil, S Biricik, S Bayhan… - IEEE Industrial …, 2020 - ieeexplore.ieee.org
In this article, we present an overview of sliding mode control (SMC) and its applications in
power converters. Owing to the distinguished features such as fast dynamic response …

Neural network-based tracking control of uncertain robotic systems: Predefined-time nonsingular terminal sliding-mode approach

Y Sun, Y Gao, Y Zhao, Z Liu, J Wang… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
This article investigates the predefined time trajectory tracking control of uncertain nonlinear
robotic systems. A radial basis function neural network (RBFNN) is used to estimate …

Sliding mode control of grid-connected neutral-point-clamped converters via high-gain observer

J Liu, X Shen, AM Alcaide, Y Yin, JI Leon… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
In this article, a nonlinear high-gain observer (NHGO)-based second-order sliding mode
(SOSM) control strategy is proposed for the three-phase three-level neutral-point-clamped …

New chaotic memristive cellular neural network and its application in secure communication system

C **u, R Zhou, Y Liu - Chaos, Solitons & Fractals, 2020 - Elsevier
In order to improve the engineering feasibility of the memristive cellular neural network, a
new memristor model with the smooth characteristic curve is designed. Based on the new …

Cascade control of grid-connected NPC converters via sliding mode technique

X Shen, J Liu, H Lin, Y Yin… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
This paper proposes a two-stage control strategy including an adaptive sliding mode control
(ASMC) and a nonlinear high-gain observer (HGO) for the three-level neutral-point-clamped …

[HTML][HTML] artificial intelligence control system applied in smart grid integrated doubly fed induction generator-based wind turbine: A review

RK Behara, AK Saha - Energies, 2022 - mdpi.com
Wind-driven turbines utilizing the doubly-fed induction generators aligned with the
progressed IEC 61400 series standards have engrossed specific consideration as of their …